Development Principles for Biotech Data Teams


Imagine it's your first day leading the data team at a biotech startup. Maybe your title includes words like """"computational biology"""" or """"bioinformatics"""". Or maybe it leans more towards """"data science"""" or """"machine learning"""". Either way, expectations are high: We all know that AI is on its way to revolutionizing drug discovery. At your competitors, it already has. Or at least that's what your CEO believes. You were hired for this role because you understand the """"tech"""" side. You know how to write software, build predictive models, turn data into insights. You understand digital technology better than anyone at the company you just joined. But here's the catch: The biggest problems you're about to face aren't technology problems.

As a leader of a data team in a biotech organization, it isn't enough to build systems that will support your organization. You need to build an organization that can use those systems to become more than the sum of its parts. This talk will present twelve principles designed to guide leaders of Biotech Data teams through this journey. Inspired by the Agile Manifesto, but deliberately tailored to this new context, these twelve principles will help your team address three key areas:
- Driving organizational strategy at a broader scope by adopting scientific rather than purely technical objectives
- Collaborating more effectively with wet lab teams by adjusting communication patterns and attitudes
- Aligning development practices more closely with the needs of the organization.

This presentation is aimed at technical leaders in biotech organizations who are ready to take on the challenge of making their data teams, their bench scientists and everyone in between work more effectively with data and digital tools. Maybe you entered biotech from a tech background. Or maybe you became a data expert starting from a background in biology or chemistry. Either way, if you know what an organization that uses data effectively looks like, the principles in this presentation will help you build that within your own organization.


Jesse Johnson is Vice President of Data Science and Data Engineering at Dewpoint Therapeutics, a drug development Biotech startup founded in 2019 around a scientific field called biomolecular condensates. In this role, Jesse's diverse set of experiences from academic math departments, engineering teams at Google, and data science teams at large, medium and small life science companies provide a unique perspective on the ways that data and wet lab teams communicate differently, or sometimes don't communicate at all.

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